DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/05/2026 has been entered.
Status of claims
Claim 19 is canceled.
Claims 20-21 are newly added.
Claims 1-18,20-21 are pending.
Response to arguments
With respect to Applicant’s remarks filed on 05/05/2026 and 06/05/2026; Applicant's “Amendments and Remarks” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
Applicant remarks:
Arguments should overcome 35 U.S.C. 101 rejection.
New claims 20-21 clarify the 35 U.S.C. 112(b) rejection.
Huo does not teach “Kinds of means of transportation”.
Office Response:
Argument overcomes 35 U.S.C. 101 rejection.
35 U.S.C. 112(b) rejection overcome based on the new claims 20-21.
Please see the new mapping of the specific “Kinds of means of transportation”.
Applicant further argues that the other independent claims which recite similar features are allowable and the dependent claims are also allowable since they depend on allowable subject and the Office respectfully disagrees. It is the Office's stance that all the claimed subject matter has been properly rejected; therefore, the Office's respectfully disagrees with applicant’s arguments.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1,3-4,6, 17-18 are rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”).
Regarding claim 1, Froment teaches A people-flow analysis apparatus that analyzes people-flow data using location information from mobile terminals, comprising: processing circuitry configured to: (See Froment [column 3 lines 17-20] the media device 102(D) may be referred to as an information processing system or an information processing device)
read, along with time information, location information estimated based on communication performed by a plurality of mobile terminals with a positioning apparatus, from a database in which the location information is accumulated; (See Froment [column 2 line 23-26 ] The historical data may include time data which may indicate times and dates associated with the content usage data, the location data, or other device usage data.)
generate, for the cleansed location information, trip data indicating travel paths of users carrying the mobile terminals; (See Froment [column 4] In FIG. 1, the server 104 includes a travel route pattern generation module 122 configured to generate travel route pattern data 124 representative of travel route patterns. The travel route patterns may be described as consistent sequences of geographic points through which the users 106(U) or the media devices 102(D) pass while travelling, for example, by common carrier or public transportation. For example, a particular travel route pattern for a particular user 106(U) may be determined once the particular user 106(U) of a particular media device 102(D) travels on the same train route at least fifteen times within a month.)
determine, for the generated trip data, kinds of means of transportation of the users used in the travel path (See Froment [column 7 lines 4-8] The travel route pattern generation module 122 may be configured to determine a type of transportation used by the user 106(U) based on the location data 118. ) by matching traffic base points to center coordinates of a mesh area corresponding to the trip data among mesh areas partitioned for at least one predetermined region with respect to the generated trip data, (See Froment column 4 The travel route pattern data 124 may be generated based on the location data 118 stored as the historical data 110 by the server 104. The travel route pattern data 124 may be generated based on the location data 118 and the time data 120 which are stored as the historical data 110.)
wherein said matching comprises, for a given traffic base point, matching the traffic base point to a facility used as a start or a goal for a kind of means of transportation used in the travel path (See Froment column 12the server 104 determines a correspondence of the first user account and the second user account based on a weighted statistical analysis. For example, the server 104 may assign different weight values to matching content usage data 116 and matching travel route pattern data 124)
However, Froment does not expressly disclose or otherwise teach perform cleansing processing for thinning out, integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh. Nevertheless, in a related field of invention, Huo teaches perform cleansing processing for thinning out, according to a predetermined rule, the location information received by the positioning apparatus (See Huo the step 4 includes: Duplicate removal processing is carried out to realize data cleansing to the initial data using data operation modules, obtains described first Data.)
integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh.
(see Huo at least After shortest path between two continuous points, decile divides traveling time, and the time after dividing equally is added to the shifting of each edge On dynamic time table. If Number is supported in the connection that adjacent mesh is calculated>=Smallest connection supports number, merges, and makes the grid being newly added after merging Centered on grid its adjacent mesh of recursive calculation again, recurrence, terminates until being unsatisfactory for consolidation strategy.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Huo’s filtering big data system and location based service in order to allow to greatly reduces the burden of real-time computing on the server terminal and The method adopted by the algorithm to reduce the amount of calculation and facilitate data modeling is map gridding (See Huo “Data processing process”).
Regarding claim 3, Froment and Huo remain applied as claim 1. Froment teaches wherein in reading the location information, the processing circuitry configured to set different reference time periods for date and time of obtainment of the location information and for date and time of evaluation of the location information(see Froment [column 4 lines 21-24] The time data 120 may include data which indicates location times and dates associated with the locations of the media device 102(D).
Regarding claim 4, Froment and Huo remain applied as claim 1. Froment teaches wherein in performing the cleansing processing, the processing circuitry configured to perform processing of eliminating a location information item indicating a location identical with a location of another location information item (See Froment column 16 In one example, travel route patterns overlap when at least a portion of the travel route patterns coincide with one another. In another example, the travel route patterns may overlap one another when the travel route patterns pass through the same locations at the same times, it is obvious that one can eliminate overlap data for cleaning the data as a predetermined rule).
Regarding claim 6, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach to perform processing of eliminating a location information item indicating a length of stay in a predetermined area shorter than a predetermined threshold. Nevertheless, in a related field of invention, Huo teaches to perform processing of eliminating a location information item indicating a length of stay in a predetermined area shorter than a predetermined threshold. (See Huo From the first data, select a plurality of activity location stay points of the user within a fixed period, construct a sequence of activity stay points of the user, and record the user's activity time, see Abstract clustering, according to user analysis results, time, location Service recommendation, Therefore, the main advantage of grid merging is to reduce the scale of the roadmap model and reduce the time spent in the process of finding the shortest path without losing reliability.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Huo’s filtering big data system and location based service in order to allow to greatly reduces the burden of real-time computing on the server terminal and The method adopted by the algorithm to reduce the amount of calculation and facilitate data modeling is map gridding (See Huo “Data processing process”).
Regarding claim 17, Froment teaches location information from mobile terminals, the method to be executed by a computer including a processing circuitry(See Froment [column 3 lines 17-20] the media device 102(D) may be referred to as an information processing system or an information processing device)
, the method causing the processing circuitry to perform to: read, along with time information, location information estimated based on communication performed(See Froment [column 2 line 23-26 ] The historical data may include time data which may indicate times and dates associated with the content usage data, the location data, or other device usage data.)
by a plurality of mobile terminals with a positioning apparatus (See Froment column 9 The satellite-based system may include one or more of a Global Positioning System receiver, a GLONASS (Global Navigation Satellite System) receiver, a Galileo receiver, an Indian Regional Navigational Satellite System, and so forth. );
generate, for the cleansed location information, trip data indicating travel paths of users carrying the mobile terminals; (See Froment [column 4] In FIG. 1, the server 104 includes a travel route pattern generation module 122 configured to generate travel route pattern data 124 representative of travel route patterns. The travel route patterns may be described as consistent sequences of geographic points through which the users 106(U) or the media devices 102(D) pass while travelling, for example, by common carrier or public transportation. For example, a particular travel route pattern for a particular user 106(U) may be determined once the particular user 106(U) of a particular media device 102(D) travels on the same train route at least fifteen times within a month.)
determine, for the generated trip data, kinds of means of transportation of the users used in the travel path by matching traffic base points to center coordinates of a mesh area corresponding to the trip data among mesh areas partitioned for at least one predetermined region with respect to the generated trip data; (See Froment column 4 The travel route pattern data 124 may be generated based on the location data 118 stored as the historical data 110 by the server 104. The travel route pattern data 124 may be generated based on the location data 118 and the time data 120 which are stored as the historical data 110.)
store a database of traffic base points and information associated with the database of traffic base points including identification of facilities (See column 2 The travel may be on foot, bicycle, automobile, common carrier, public transportation, and so forth. For example, the location data indicative of a position on train tracks may indicate the user is commuting using a train along a particular route..) corresponding to the traffic base points, wherein said matching comprises, for a given traffic base point, matching the traffic base point, in the database, to a facility used as a start or a goal for a kind of means of transportation used in the travel path (See Froment column 12the server 104 determines a correspondence of the first user account and the second user account based on a weighted statistical analysis. For example, the server 104 may assign different weight values to matching content usage data 116 and matching travel route pattern data 124)
However, Froment does not expressly disclose or otherwise teach perform cleansing processing for thinning out, according to a predetermined rule, the location information received by the positioning apparatus; integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh. Nevertheless, in a related field of invention, Huo teaches perform cleansing processing for thinning out, according to a predetermined rule, the location information received by the positioning apparatus; (See Huo the step 4 includes: Duplicate removal processing is carried out to realize data cleansing to the initial data using data operation modules, obtains described first Data.)
integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh. (see Huo at least After shortest path between two continuous points, decile divides traveling time, and the time after dividing equally is added to the shifting of each edge On dynamic time table. If Number is supported in the connection that adjacent mesh is calculated>=Smallest connection supports number, merges, and makes the grid being newly added after merging Centered on grid its adjacent mesh of recursive calculation again, recurrence, terminates until being unsatisfactory for consolidation strategy.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Huo’s filtering big data system and location based service in order to allow to greatly reduces the burden of real-time computing on the server terminal and The method adopted by the algorithm to reduce the amount of calculation and facilitate data modeling is map gridding (See Huo “Data processing process”).
Regarding claim 18, Froment teaches A people-flow analysis system that comprises a processor of a computer and analyzes people-flow data using location information from mobile terminals, the processor of the computer comprising(See Froment [column 3 lines 17-20] the media device 102(D) may be referred to as an information processing system or an information processing device)
: a module that is configured to read, along with time information, location information estimated based on communication performed by a plurality of mobile terminals(See Froment [column 2 line 23-26 ] The historical data may include time data which may indicate times and dates associated with the content usage data, the location data, or other device usage data.)
with a positioning apparatus(See Froment column 9 The satellite-based system may include one or more of a Global Positioning System receiver, a GLONASS (Global Navigation Satellite System) receiver, a Galileo receiver, an Indian Regional Navigational Satellite System, and so forth. );
according to a predetermined rule, the location information received by the positioning apparatus; (See Froment [column 2 line 23-26 ] The historical data may include time data which may indicate times and dates associated with the content usage data, the location data, or other device usage data.)
a module that is configured to generate, for the cleansed location information, trip data indicating travel paths of users carrying the mobile terminals(See Froment [column 4] In FIG. 1, the server 104 includes a travel route pattern generation module 122 configured to generate travel route pattern data 124 representative of travel route patterns. The travel route patterns may be described as consistent sequences of geographic points through which the users 106(U) or the media devices 102(D) pass while travelling, for example, by common carrier or public transportation. For example, a particular travel route pattern for a particular user 106(U) may be determined once the particular user 106(U) of a particular media device 102(D) travels on the same train route at least fifteen times within a month.);and
a module that is configured to determine, for the generated trip data, kinds of means of transportation of the users used in the travel path(See Froment [column 7 lines 4-8] The travel route pattern generation module 122 may be configured to determine a type of transportation used by the user 106(U) based on the location data 118. ) by matching traffic base points to center coordinates of a mesh area corresponding to the trip data among mesh areas partitioned for at least one predetermined region with respect to the generated trip data(See Froment column 4 The travel route pattern data 124 may be generated based on the location data 118 stored as the historical data 110 by the server 104. The travel route pattern data 124 may be generated based on the location data 118 and the time data 120 which are stored as the historical data 110.)
; wherein the system further comprises a database of traffic base points and information associated with the database of traffic base points including identification of facilities corresponding to the traffic base points; (See column 2 The travel may be on foot, bicycle, automobile, common carrier, public transportation, and so forth. For example, the location data indicative of a position on train tracks may indicate the user is commuting using a train along a particular route)
wherein said matching, by the module of the processor, comprises, for a given traffic base point, matching the traffic base point, in the database, to a facility used as a start or a goal for a kind of means of transportation used in the travel path (See Froment column 12the server 104 determines a correspondence of the first user account and the second user account based on a weighted statistical analysis. For example, the server 104 may assign different weight values to matching content usage data 116 and matching travel route pattern data 124)
However, Froment does not expressly disclose or otherwise teach perform cleansing processing for thinning out, according to a predetermined rule, the location information received by the positioning apparatus; integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh. Nevertheless, in a related field of invention, Huo teaches perform cleansing processing for thinning out, according to a predetermined rule, the location information received by the positioning apparatus; (See Huo the step 4 includes: Duplicate removal processing is carried out to realize data cleansing to the initial data using data operation modules, obtains described first Data.)
integrate two or more of the mesh areas after the mesh areas are partitioned for the predetermined region and provide a resulting integrated mesh data structure in which the two or more mesh areas are combined into a single integrated mesh. (see Huo at least After shortest path between two continuous points, decile divides traveling time, and the time after dividing equally is added to the shifting of each edge On dynamic time table. If Number is supported in the connection that adjacent mesh is calculated>=Smallest connection supports number, merges, and makes the grid being newly added after merging Centered on grid its adjacent mesh of recursive calculation again, recurrence, terminates until being unsatisfactory for consolidation strategy.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Huo’s filtering big data system and location based service in order to allow to greatly reduces the burden of real-time computing on the server terminal and The method adopted by the algorithm to reduce the amount of calculation and facilitate data modeling is map gridding (See Huo “Data processing process”).
Claims 2,8, 13-16 are rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and US20190028852A1 to Yamada (herein after “Yamada”).
Regarding claim 2, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach the processing circuitry further configured to: calculate, for performing scale-up estimation from a number of samples of the location information to a population of an estimation area, a scale-up factor for scaling up a number of mobile terminals being used to the population of the estimation area. Nevertheless, in a related field of invention, Yamada teaches the processing circuitry further configured to: calculate, for performing scale-up estimation from a number of samples of the location information to a population of an estimation area, a scale-up factor(see Yamada same as proportionality factor ) for scaling up a number of mobile terminals being used to the population of the estimation area (see Yamada para[0017] In the population estimating apparatus described above, the relation parameter deriving unit may have a proportionality factor deriving unit to derive a proportionality factor from the local area by dividing the population of the local area indicated by the local population information by the number of wireless terminals extracted by the second terminal extracting unit. In the population estimating apparatus described above, the relation parameter deriving unit may have a correction unit to correct the proportionality factor based on the wide area population information and derive the relation parameter.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017].
Regarding claim 8, Froment and Huo remain applied as claim 1. Nevertheless, Yamada same field of endeavor teaches wherein in generating the trip data (see Yamada movement history), the processing circuitry configured to calculate an amount of displacement of the location information over time and classifying a location information item as stay or travel (see Yamada para[0098] (b) a moving distance of the communication terminal 110 in the geographic range and time indicated by the input information;; para[0066] a population movement survey, population estimation, statics on the immigration control, an estimation survey on the numbers of tourists and nights of their stay, a survey on regional movement of passengers, or the like, which are published by an administrative agency.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017].
Regarding claim 13, Froment and Huo remain applied as claim 1 Nevertheless, Yamada same field of endeavor teaches wherein the processing circuitry further configured to using master data that stores traffic base points and associated partitioned areas corresponding to predetermined regions, estimate a candidate for a used traffic base point by searching, based on the location information, the partitioned areas associated with the traffic base points. (See Yamada [0065], [0067], [0076] In this case, it is possible to more accurately estimate a population by deriving a relation parameter of a particular facility, using an entry/exit record, a visitor record, a guest record, POS data or the like of the particular facility for example., para[0120])
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017].
Regarding claim 14, Froment and Huo remain applied as claim 1, Froment, Huo and Yamada remain applied as claim 2. Yamada teaches wherein in calculate a scale-up factor (see Yamada same as proportionality factor ) for each integrated area , the plurality of integrated areas including the integrated mesh data structure, wherein the two or more mesh areas to be integrated are selected to be integrated based on comparison(See Huo step 6.3 Through the similarity in time and space, some adjacent meshes are merged to form an independent local region set; next, we analyze the strategy of mesh merge) of the two or more mesh area to a predetermined size(See Yamada para[0037] a division made by subdividing an area by an unit region with a predetermined size and shape (which may be referred to as an area mesh or the like), etc), wherein the scale up factor is calculated for each determined means of transportation (see Yamada para[0017] In the population estimating apparatus described above, the relation parameter deriving unit may have a proportionality factor deriving unit to derive a proportionality factor from the local area by dividing the population of the local area indicated by the local population information by the number of wireless terminals extracted by the second terminal extracting unit; same as ).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017] and with Huo’s filtering big data system and location based service in order to allow to greatly reduces the burden of real-time computing on the server terminal and The method adopted by the algorithm to reduce the amount of calculation and facilitate data modeling is map gridding (See Huo “Data processing process”).
Regarding claim 15, Froment, Huo and Yamada remain applied as claim 2. Yamada teaches wherein in calculating the scale-up factor (see Yamada same as proportionality factor ), the processing circuitry calculate a corrected factor for each integrated partitioned area based on a number of traffic-facility users and a corrected number of users(see Yamada para[0017] the relation parameter deriving unit may have a correction unit to correct the proportionality factor based on the wide area population information and derive the relation parameter).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017]).
Regarding claim 16, Froment, Huo and Yamada remain applied as claim 2. Yamada teaches wherein in calculating the scale-up factor (same as proportionality factor ), the processing circuitry set a screen line for each of municipal codes, expressway traffic sections, air routes, and railway facilities having ticket barriers to be passed through, the screen line indicating a boundary expected to be passed through by travel means(see Yamada para[0091] a log information interpolating unit 314 first generates one or more pieces of log information such that positions indicated by one or more pieces of log information generated by an interpolation process is arranged at a regular interval on the straight line connecting the positions indicated by the two pieces of log information described above; para[0041] an output apparatus such as a display apparatus ); and calculating, for each travel means, a screen line passing count that indicates a number of times the screen line is passed through (see Yamada para[0091] [0091] If at least one of the positions indicated by the positional information of the two pieces of log information is arranged on a road, on a rail, or on a route, the log information interpolating unit 314 may also generate one or more pieces of log information such that the position indicated by the log information generated by the interpolation is arranged on the road,).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Yamada’s scale-up factor based on number of the mobile terminal present in order to allow to correct the proportionality factor based on the wide area population information and derive the relation parameter (Yamada para[0017]).
Claims 9, and 11 are rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and JP2001101563A to Asakura et al. (herein after “Asakura”).
Regarding claim 9, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach wherein in generating the trip data, the processing circuity configured to integrate the location data items into a single trip data item if sequential location data items are apart by a distance not longer than a threshold and are classified as stay. Nevertheless, in a related field of invention, Asakura teaches wherein in generating the trip data the processing circuity configured to integrate the location data items into a single trip data item if sequential location data items are apart by a distance not longer than a threshold and are classified as stay (see Asakura para [0018] FIG. 4 shows position data of the subject during movement, which is processed by the data processing device of this embodiment. FIG. 4 shows two movements (trips) of the subject (sequence numbers 1 to 23 show the first movement of the subject, and sequence numbers 24 to 42 show the second movement). The position data between the sequence numbers 23 and 24 while the subject is staying (when the subject is not moving) is thinned out by the above processing).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Asakura’s position data between two sequence numbers classified as stay in order to allow to accurately acquire the traffic behavior of the subject in order to properly predict (see Asakura para[0002]).
Regarding claim 11, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach wherein in determining the means of transportation of the users, the processing circuitry configured to determine the means of transportation after adding traffic section information and traffic facility information to the location information. Nevertheless, in a related field of invention, Asakura teaches wherein in determining the means of transportation of the users, the processing circuitry configured to determine the means of transportation after adding traffic section information and traffic facility information to the location information (see Asakura para [0015] The facility database 23 is stored. In the geographic information database 21, transportation networks such as roads and railways are registered. In the ID attribute database 22, personal information such as the home or work address of each subject is registered.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Asakura’s position data between two sequence numbers classified as stay in order to allow to accurately acquire the traffic behavior of the subject in order to properly predict (see Asakura para[0002]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and JP2014122841A to Ejima et al. (herein after “Ejima”).
Regarding claim 10, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach wherein in determining the means of transportation of the users, the processing circuitry configured to determine the means of transportation after adding traffic section information and traffic facility information to the location information. Nevertheless, in a related field of invention, Ejima teaches wherein in determining the means of transportation of the users, the processing circuity configured to determine air travel based on the location information before determining other means of transportation (see Ejima para[0242] Determine that the user is traveling by plane. If the user is traveling by plane, it is safe for the HMD1 user to fall asleep except for special occupations such as a pilot. Therefore, when the vehicle detection unit 309 determines that the user is moving by an airplane (Step S613; Yes), the process proceeds to Step S614, and when it is determined that the user is not moving by an airplane (Step S613; No). ), Go to step S615).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Ejima’s determine air travel based on the location information before determining other means of transportation in order to allow to guides the route from the departure point to the destination point according to the moving means of the user (see Ejima para[0002]).
Claims 5 and 7 are rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and US 20090093924 A to Aso(herein after “Aso”).
Regarding claim 5, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach to perform processing of checking displacement angles of the location information over time on a map, and if a displacement angle smaller than a predetermined threshold is detected, eliminating a location information item corresponding to a vertex of the displacement angle. Nevertheless, in a related field of invention, Aso teaches to perform processing of checking displacement angles of the location information over time on a map, and if a displacement angle smaller than a predetermined threshold is detected, eliminating a location information item corresponding to a vertex of the displacement angle. (See Aso para [0031] The control unit 50 has the above-described Kalman filter 200 function and a function for steering the vehicle. Prediction calculation of state quantities representing the movement of the vehicle in the lateral direction (yaw rate, yaw angle, lateral displacement speed, and lateral position) is performed by the Kalman filter 200 function,).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Aso’s filtering data based on displacement angle in order to allow to improve the accuracy of predicting the state quantities of the vehicle.
Regarding claim 7, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach to calculate a travel speed from an amount of displacement of the location information over time, and excluding, from thinning-out processing, a location information item indicating displacement at a speed higher than a predetermined speed. Nevertheless, in a related field of invention, Aso teaches to calculate a travel speed from an amount of displacement of the location information over time, and excluding, from thinning-out processing, a location information item indicating displacement at a speed higher than a predetermined speed. (See Aso para [0031] The control unit 50 has the above-described Kalman filter 200 function and a function for steering the vehicle. Prediction calculation of state quantities representing the movement of the vehicle in the lateral direction (yaw rate, yaw angle, lateral displacement speed, and lateral position) is performed by the Kalman filter 200 function,).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Aso’s filtering data based on displacement angle in order to allow to improve the accuracy of predicting the state quantities of the vehicle.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and CN 110720026 A to Rubin et al.(herein after “Rubin”).
Regarding claim 12, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach wherein in determining the means of transportation of the users, the processing circuitry configured to: set, for each trip data item, a start and a goal for each of a plurality of travel means, identify a plurality of routes allowing travel from the start to the goal at a travel speed of the travel means. Nevertheless, in a related field of invention, Rubin teaches wherein in determining the means of transportation of the users, the processing circuitry configured to : set, for each trip data item, a start and a goal for each of a plurality of travel means (See Rubin the mapping application server provides an application programming interface (API) for accessing a map and navigation data to display a digital map, and providing to the navigation guidance of the destination position (direction). a digital map) , identify a plurality of routes allowing travel from the start to the goal at a travel speed of the travel means (See Rubin transportation traffic mode, bus service, recommendation, which may include multiple traffic modes based on shortest duration, distance, or the lowest cost to reach the destination position) to provide navigation or travel guidance);
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Rubin’s selecting trip data based on lowest-cost in order to allow to provide a digital map of a geographic area, where the digital map includes a user's pick-up location, destination location, navigation guidance to travel to the destination location, and the like (See Rubin’s second paragraph).
Claims 20-21 are rejected under 35 U.S.C. 103 as being unpatented over US 9456043 B1 to Froment et al. (herein after “Froment”) in view of CN108737492A to Huo et al. (herein after “Huo”) and US20080281513A1 to Sakai (herein after “Sakai”).
Regarding claim 20, Froment and Huo remain applied as claim 1. However, Froment does not expressly disclose or otherwise teach comprising subsequently retrieving master data of the traffic base points by referencing one or more mesh codes associated with stored traffic base points. Nevertheless, Sakai same field of endeavor teaches comprising subsequently retrieving master data of the traffic base points by referencing one or more mesh codes associated with stored traffic base points(See Sakai para[0026] Further, the data records of the candidate facilities that were extracted on the basis of the area codes are checked with the searched mesh codes and the candidate facilities that belong to the mesh areas within the narrowed search range are extracted).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Sakai’s extracting data based on mesh code in order to allow to narrow a search to facilities that are located within a specific area (See Sakai para[0003]).
Regarding claim 21, Froment and Huo remain applied as claim 1. Froment teaches wherein: the at least one predetermined region is at least one administrative area selected from one of a city, ward, town, or village; (See Froment [columns 1-2]The historical data may include location data associated with the media devices. The location data may indicate a geographic location (“geolocation”) comprising a latitude and longitude of the media device, a relative location such as on a particular train car, building, conference room, dorm room, county, city)
However, Froment does not expressly disclose or otherwise teach wherein mesh areas are provided as subdivisions of the at least one predetermined region, that have an initial area smaller than a size of the facility such that the facility initially is placed into at least two of the mesh areas; wherein the two or more mesh areas to be integrated are selected to be integrated based on comparison of the two or more mesh areas to a predetermined size, comprising identifying whether each of the two or more mesh areas would be smaller than a threshold defined in the apparatus prior to such identifying, and integrating the two or more mesh areas based on at least one of the mesh areas being smaller than the threshold. Nevertheless, Sakai same field of endeavor teaches wherein mesh areas are provided as subdivisions of the at least one predetermined region (See Sakai para[0026]To extract the candidate facilities which are located within the narrowed search range, area codes of administrative areas and mesh codes of mesh areas (subdivision plat areas) which are both located within the specified narrowed search range are searched for. )
that have an initial area smaller than a size of the facility such that the facility initially is placed into at least two of the mesh areas; wherein the two or more mesh areas to be integrated are selected to be integrated based on comparison of the two or more mesh areas to a predetermined size, comprising identifying whether each of the two or more mesh areas would be smaller than a threshold defined in the apparatus prior to such identifying, and integrating the two or more mesh areas based on at least one of the mesh areas being smaller than the threshold.(See Sakai claim 1 sequentially narrows down and displays candidate facilities according to a narrowing condition from a first data table that stores facility information including area information on which facilities exist,, see The mesh area is partitioned so that the boundary line between adjacent mesh areas is parallel to the latitude and longitude lines, para[0037] FIG. 4 is a diagram showing an example of the mesh area. As shown in FIG. 4, the mesh areas have no relation with the administrative areas and are small square areas (meshes), into which map data is subdivided. Each mesh area is much smaller than one administrative area (sectioned range). According to the current example, for example, one mesh area is a square, 2.5 km on a side.)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine Froment’s systems, devices and method of using location data from the mobile terminal to determine the kind of transportation along the travel path with Sakai’s extracting data based on mesh code in order to allow to narrow a search to facilities that are located within a specific area (See Sakai para[0003]).
Conclusion
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/NAZIA AFRIN/Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
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